Example notebook (spinal data)¶
1: Read and organize anatomical data¶
Data used in notebook is avilable here.
!wget -O spinalcord_results.zip https://github.com/courtois-neuromod/anat-processing/releases/download/r20210610/spinalcord_results.zip
!unzip -j spinalcord_results.zip -d ./spinalcord_results/
2: Plot data¶
import plotly.graph_objects as go
import plotly.tools as tls
from plotly.offline import plot, iplot, init_notebook_mode
from plotly.validators.scatter.marker import SymbolValidator
from IPython.core.display import display, HTML
import numpy as np
import pandas as pd
# Add plotly
init_notebook_mode(connected = True)
config={'showLink': False, 'displayModeBar': False}
# Load the data
df_t1 = pd.read_csv("./spinalcord_results/csa-SC_T1w.csv", converters={'project_id': lambda x: str(x)})
df_t2 = pd.read_csv("./spinalcord_results/csa-SC_T2w.csv", converters={'project_id': lambda x: str(x)})
# Insert new columns for Subject and Session and start inserting values
df_t1.insert(0, "Subject", "Any")
df_t1.insert(1, "Session", "Any")
# Get Subject and Session from csv
for index, row in df_t1.iterrows():
subject = int(row['Filename'].split("/")[6].split('-')[1])
session = int(row['Filename'].split("/")[7].split("-")[1])
df_t1.at[index, 'Subject'] = subject
df_t1.at[index, 'Session'] = session
# Sort values based on Subject -- Session
df_2 = df_t1.sort_values(['Subject', 'Session'], ascending=[True, True])
# Define lists for metrics
mean_area_matrix_1 = []
mean_ap_matrix_1 = []
mean_rl_matrix_1 = []
mean_angle_matrix_1 = []
# Get the values for all 4 metric [area, mean_AP, mean_RL, angle_AP]
for i in range(0, 6, 1):
sub_values = df_2.loc[df_2['Subject'] == i+1]
mean_area_ses = []
mean_ap_ses = []
mean_rl_ses = []
mean_angle_ses = []
for j in range(0, 4, 1):
ses_values = sub_values.loc[sub_values['Session'] == j+1]
mean_area = -100
mean_ap = -100
mean_rl = -100
mean_angle = -100
for index, row in ses_values.iterrows():
# Read values
MEAN_area = row['MEAN(area)']
MEAN_diameter_AP = row['MEAN(diameter_AP)']
MEAN_diameter_RL = row['MEAN(diameter_RL)']
MEAN_angle_AP = row['MEAN(angle_AP)']
# Store values
mean_area = MEAN_area
mean_ap = MEAN_diameter_AP
mean_rl = MEAN_diameter_RL
mean_angle = MEAN_angle_AP
# Append values to lists for sessions
mean_area_ses.append(mean_area)
mean_ap_ses.append(mean_ap)
mean_rl_ses.append(mean_rl)
mean_angle_ses.append(mean_angle)
# Append session lists to main matrices for each metric
mean_area_matrix_1.append(mean_area_ses)
mean_ap_matrix_1.append(mean_ap_ses)
mean_rl_matrix_1.append(mean_rl_ses)
mean_angle_matrix_1.append(mean_angle_ses)
# Insert new columns for Subject and Session and start inserting values
df_t2.insert(0, "Subject", "Any")
df_t2.insert(1, "Session", "Any")
# Get Subject and Session from csv
for index, row in df_t2.iterrows():
subject = int(row['Filename'].split("/")[6].split('-')[1])
session = int(row['Filename'].split("/")[7].split("-")[1])
df_t2.at[index, 'Subject'] = subject
df_t2.at[index, 'Session'] = session
# Sort values based on Subject -- Session
df_3 = df_t2.sort_values(['Subject', 'Session'], ascending=[True, True])
# Define lists for metrics
mean_area_matrix_2 = []
mean_ap_matrix_2 = []
mean_rl_matrix_2 = []
mean_angle_matrix_2 = []
# Get the values for all 4 metric [area, mean_AP, mean_RL, angle_AP]
for i in range(0, 6, 1):
sub_values = df_3.loc[df_3['Subject'] == i+1]
mean_area_ses = []
mean_ap_ses = []
mean_rl_ses = []
mean_angle_ses = []
for j in range(0, 4, 1):
ses_values = sub_values.loc[sub_values['Session'] == j+1]
mean_area = -100
mean_ap = -100
mean_rl = -100
mean_angle = -100
for index, row in ses_values.iterrows():
# Read values
MEAN_area = row['MEAN(area)']
MEAN_diameter_AP = row['MEAN(diameter_AP)']
MEAN_diameter_RL = row['MEAN(diameter_RL)']
MEAN_angle_AP = row['MEAN(angle_AP)']
# Store values
mean_area = MEAN_area
mean_ap = MEAN_diameter_AP
mean_rl = MEAN_diameter_RL
mean_angle = MEAN_angle_AP
# Append values to lists for sessions
mean_area_ses.append(mean_area)
mean_ap_ses.append(mean_ap)
mean_rl_ses.append(mean_rl)
mean_angle_ses.append(mean_angle)
# Append session lists to main matrices for each metric
mean_area_matrix_2.append(mean_area_ses)
mean_ap_matrix_2.append(mean_ap_ses)
mean_rl_matrix_2.append(mean_rl_ses)
mean_angle_matrix_2.append(mean_angle_ses)
# Functions for mean and std
def get_mean(mean_matrix):
temp = mean_matrix[::]
mean_list = []
for ele in temp:
ele = [i for i in ele if i!=-100]
mean_list.extend(ele)
mean = float('{0:.2f}'.format(np.mean(mean_list)))
return mean
def get_std(mean_matrix):
temp = mean_matrix[::]
mean_list = []
for ele in temp:
ele = [i for i in ele if i!=-100]
mean_list.extend(ele)
std = float('{0:.3f}'.format(np.std(mean_list)))
return std
# Get different symbols (See for reference: https://plotly.com/python/marker-style/)
raw_symbols = SymbolValidator().values
namestems = []
namevariants = []
symbols = []
for i in range(0,len(raw_symbols),3):
name = raw_symbols[i+2]
symbols.append(raw_symbols[i])
namestems.append(name.replace("-open", "").replace("-dot", ""))
namevariants.append(name[len(namestems[-1]):])
# Load fancy colors
tableau20 = [(31, 119, 180), (174, 199, 232), (255, 127, 14), (255, 187, 120),
(44, 160, 44), (152, 223, 138), (214, 39, 40), (255, 152, 150),
(148, 103, 189), (197, 176, 213), (140, 86, 75), (196, 156, 148),
(227, 119, 194), (247, 182, 210), (127, 127, 127), (199, 199, 199),
(188, 189, 34), (219, 219, 141), (23, 190, 207), (158, 218, 229)]
# Define lists needed for plotting
t1 = [-0.2, -0.06, 0.08, 0.22]
t2 = [0 -0.2 + i*0.14 for i in range(0, 4)]
labels =["Session 1", "Session 2","Session 3","Session 4"]
labels_subjects = ['Subject 1', 'Subject 2', 'Subject 3', 'Subject 4', 'Subject 5', 'Subject 6']
labels_int = [i for i in range(1, 7)]
x_rev = labels_int[::-1]
# Add first values for labels [Sub1...Sub6]
figb = go.Figure(data=go.Scatter(x=labels_int,
y=[-1000, -1000, -1000, -1000, -1000, -1000],
mode='markers',
showlegend=False,
marker_color='red'))
# Add MEAN [area] --- > T1w
for trace in range(0, len(mean_area_matrix_1)):
t = [trace -0.2 + i*0.14 for i in range(0, 4)]
if trace == 0:
figb.add_trace(go.Scatter(x=t,
y=mean_area_matrix_1[trace],
mode='markers',
legendgroup="group1",
hovertemplate =
"Mean (area): <i> %{y: .2f} </i> mm<sup>2</sup>" +
"<br>" +
"<b>%{text}</b>",
showlegend = True,
text = ['Session {}'.format(i + 1) for i in range(4)],
name= 'T<sub>1</sub>w',
marker_color="rgb"+str(tableau20[0])))
else:
figb.add_trace(go.Scatter(x=t,
y=mean_area_matrix_1[trace],
mode='markers',
legendgroup="group1",
showlegend = False,
hovertemplate =
"Mean (area): <i> %{y: .2f} </i> mm<sup>2</sup>" +
"<br>" +
"<b>%{text}</b>",
text = ['Session {}'.format(i + 1) for i in range(4)],
name='T<sub>1</sub>w',
marker_color="rgb"+str(tableau20[0])))
# Add MEAN [area] --- > T2w
for trace in range(0, len(mean_area_matrix_2)):
t = [trace -0.2 + i*0.14 for i in range(0, 4)]
if trace == 0:
figb.add_trace(go.Scatter(x=t,
y=mean_area_matrix_2[trace],
mode='markers',
legendgroup="group2",
hovertemplate =
"Mean (area): <i> %{y: .2f} </i> mm<sup>2</sup>" +
"<br>" +
"<b>%{text}</b>",
showlegend = True,
text = ['Session {}'.format(i + 1) for i in range(4)],
name= 'T<sub>2</sub>w',
marker_symbol=symbols[5],
marker_color="rgb"+str(tableau20[3])))
else:
figb.add_trace(go.Scatter(x=t,
y=mean_area_matrix_2[trace],
mode='markers',
legendgroup="group2",
hovertemplate =
"Mean (area): <i> %{y: .2f} </i> mm<sup>2</sup>" +
"<br>" +
"<b>%{text}</b>",
showlegend = False,
text = ['Session {}'.format(i + 1) for i in range(4)],
name='T<sub>2</sub>w',
marker_symbol=symbols[5],
marker_color="rgb"+str(tableau20[3])))
# Add MEAN [AP] --- > T1w
for trace in range(0, len(mean_ap_matrix_1)):
t = [trace -0.2 + i*0.14 for i in range(0, 4)]
if trace == 0:
figb.add_trace(go.Scatter(x=t,
y=mean_ap_matrix_1[trace],
mode='markers',
visible=False,
showlegend = True,
legendgroup="group1",
hovertemplate =
"Mean [AP]: <i> %{y: .2f} </i> mm" +
"<br>" +
"<b>%{text}</b>",
text = ['Session {}'.format(i + 1) for i in range(4)],
name='T<sub>1</sub>w',
marker_color="rgb"+str(tableau20[0])))
else:
figb.add_trace(go.Scatter(x=t,
y=mean_ap_matrix_1[trace],
mode='markers',
visible=False,
showlegend = False,
legendgroup="group1",
hovertemplate =
"Mean [AP]: <i> %{y: .2f} </i> mm" +
"<br>" +
"<b>%{text}</b>",
text = ['Session {}'.format(i + 1) for i in range(4)],
name='T<sub>1</sub>w',
marker_color="rgb"+str(tableau20[0])))
# Add MEAN [AP] --- > T2w
for trace in range(0, len(mean_ap_matrix_2)):
t = [trace -0.2 + i*0.14 for i in range(0, 4)]
if trace == 0:
figb.add_trace(go.Scatter(x=t,
y=mean_ap_matrix_2[trace],
mode='markers',
visible=False,
showlegend = True,
legendgroup="group2",
hovertemplate =
"Mean [AP]: <i> %{y: .2f} </i> mm" +
"<br>" +
"<b>%{text}</b>",
marker_symbol=symbols[5],
text = ['Session {}'.format(i + 1) for i in range(4)],
name='T<sub>2</sub>w',
marker_color="rgb"+str(tableau20[3])))
else:
figb.add_trace(go.Scatter(x=t,
y=mean_ap_matrix_2[trace],
mode='markers',
visible=False,
showlegend = False,
legendgroup="group2",
hovertemplate =
"Mean [AP]: <i> %{y: .2f} </i> mm" +
"<br>" +
"<b>%{text}</b>",
marker_symbol=symbols[5],
text = ['Session {}'.format(i + 1) for i in range(4)],
name='T<sub>2</sub>w',
marker_color="rgb"+str(tableau20[3])))
# Add MEAN [RL] --- > T1w
for trace in range(0, len(mean_rl_matrix_1)):
t = [trace -0.2 + i*0.14 for i in range(0, 4)]
if trace == 0:
figb.add_trace(go.Scatter(x=t,
y=mean_rl_matrix_1[trace],
mode='markers',
visible=False,
showlegend = True,
legendgroup="group1",
hovertemplate =
"Mean (RL): <i> %{y: .2f} </i> mm" +
"<br>" +
"<b>%{text}</b>",
text = ['Session {}'.format(i + 1) for i in range(4)],
name='T<sub>1</sub>w',
marker_color="rgb"+str(tableau20[0])))
else:
figb.add_trace(go.Scatter(x=t,
y=mean_rl_matrix_1[trace],
mode='markers',
visible=False,
showlegend = False,
legendgroup="group1",
hovertemplate =
"Mean (RL): <i> %{y: .2f} </i> mm" +
"<br>" +
"<b>%{text}</b>",
text = ['Session {}'.format(i + 1) for i in range(4)],
name='T<sub>1</sub>w',
marker_color="rgb"+str(tableau20[0])))
# Add MEAN [RL] --- > T2w
for trace in range(0, len(mean_rl_matrix_2)):
t = [trace -0.2 + i*0.14 for i in range(0, 4)]
if trace == 0:
figb.add_trace(go.Scatter(x=t,
y=mean_rl_matrix_2[trace],
mode='markers',
visible=False,
showlegend = True,
legendgroup="group2",
hovertemplate =
"Mean (RL): <i> %{y: .2f} </i> mm" +
"<br>" +
"<b>%{text}</b>",
text = ['Session {}'.format(i + 1) for i in range(4)],
name='T<sub>2</sub>w',
marker_symbol=symbols[5],
marker_color="rgb"+str(tableau20[3])))
else:
figb.add_trace(go.Scatter(x=t,
y=mean_rl_matrix_2[trace],
mode='markers',
visible=False,
showlegend = False,
legendgroup="group2",
hovertemplate =
"Mean (RL): <i> %{y: .2f} </i> mm" +
"<br>" +
"<b>%{text}</b>",
text = ['Session {}'.format(i + 1) for i in range(4)],
name='T<sub>2</sub>w',
marker_symbol=symbols[5],
marker_color="rgb"+str(tableau20[3])))
# Add MEAN [angle_AP] --- > T1w
for trace in range(0, len(mean_angle_matrix_1)):
t = [trace -0.2 + i*0.14 for i in range(0, 4)]
if trace == 0:
figb.add_trace(go.Scatter(x=t,
y=mean_angle_matrix_1[trace],
mode='markers',
visible=False,
showlegend = True,
legendgroup="group1",
hovertemplate =
"Mean (angle_AP): <i> %{y: .2f} </i>°" +
"<br>" +
"<b>%{text}</b>",
text = ['Session {}'.format(i + 1) for i in range(4)],
name='T<sub>1</sub>w',
marker_color="rgb"+str(tableau20[0])))
else:
figb.add_trace(go.Scatter(x=t,
y=mean_angle_matrix_1[trace],
mode='markers',
visible=False,
showlegend = False,
legendgroup="group1",
hovertemplate =
"Mean (angle_AP): <i> %{y: .2f} </i>°" +
"<br>" +
"<b>%{text}</b>",
text = ['Session {}'.format(i + 1) for i in range(4)],
name='T<sub>1</sub>w',
marker_color="rgb"+str(tableau20[0])))
# Add MEAN [angle_AP] --- > T2w
for trace in range(0, len(mean_angle_matrix_2)):
t = [trace -0.2 + i*0.14 for i in range(0, 4)]
if trace == 0:
figb.add_trace(go.Scatter(x=t,
y=mean_angle_matrix_2[trace],
mode='markers',
visible=False,
showlegend = True,
legendgroup="group2",
hovertemplate =
"Mean (angle_AP): <i> %{y: .2f} </i>°" +
"<br>" +
"<b>%{text}</b>",
text = ['Session {}'.format(i + 1) for i in range(4)],
name='T<sub>2</sub>w',
marker_symbol=symbols[5],
marker_color="rgb"+str(tableau20[3])))
else:
figb.add_trace(go.Scatter(x=t,
y=mean_angle_matrix_2[trace],
mode='markers',
visible=False,
showlegend = False,
legendgroup="group2",
hovertemplate =
"Mean (angle_AP): <i> %{y: .2f} </i>°" +
"<br>" +
"<b>%{text}</b>",
text = ['Session {}'.format(i + 1) for i in range(4)],
name='T<sub>2</sub>w',
marker_symbol=symbols[5],
marker_color="rgb"+str(tableau20[3])))
# Calculate means
line_1 = get_mean(mean_area_matrix_1) # T1w mean area --- mean
line_2 = get_mean(mean_area_matrix_2) # T2w mean area --- mean
line_3 = get_mean(mean_ap_matrix_1) # T1w mean AP --- mean
line_4 = get_mean(mean_ap_matrix_2) # T2w mean AP --- mean
line_5 = get_mean(mean_rl_matrix_1) # T1w mean RL --- mean
line_6 = get_mean(mean_rl_matrix_2) # T2w mean RL --- mean
line_7 = get_mean(mean_angle_matrix_1) # T1w angle --- mean
line_8 = get_mean(mean_angle_matrix_2) # T2w angle --- mean
# Add dotted lines for first button
figb.add_trace(go.Scatter(x=[-1, 0, 1, 2, 3, 4, 5, 6],
y=[line_1]*8,
mode='lines',
name='T<sub>1</sub>w mean',
opacity=0.5,
line=dict(color="rgb"+str(tableau20[0]),
width=2,
dash='dot')))
figb.add_trace(go.Scatter(x=[-1, 0, 1, 2, 3, 4, 5, 6],
y=[line_2]*8,
mode='lines',
name='T<sub>2</sub>w mean',
opacity=0.5,
line=dict(color="rgb"+str(tableau20[3]),
width=2,
dash='dot')))
# Add dotted lines for second button
figb.add_trace(go.Scatter(x=[-1, 0, 1, 2, 3, 4, 5, 6],
y=[line_3]*8,
mode='lines',
visible=False,
name='T<sub>1</sub>w mean',
opacity=0.5,
line=dict(color="rgb"+str(tableau20[0]),
width=2,
dash='dot')))
figb.add_trace(go.Scatter(x=[-1, 0, 1, 2, 3, 4, 5, 6],
y=[line_4]*8,
mode='lines',
visible=False,
name='T<sub>2</sub>w mean',
opacity=0.5,
line=dict(color="rgb"+str(tableau20[3]),
width=2,
dash='dot')))
# Add dotted lines for thrid button
figb.add_trace(go.Scatter(x=[-1, 0, 1, 2, 3, 4, 5, 6],
y=[line_5]*8,
mode='lines',
visible=False,
name='T<sub>1</sub>w mean',
opacity=0.5,
line=dict(color="rgb"+str(tableau20[0]),
width=2,
dash='dot')))
figb.add_trace(go.Scatter(x=[-1, 0, 1, 2, 3, 4, 5, 6],
y=[line_6]*8,
mode='lines',
visible=False,
name='T<sub>2</sub>w mean',
opacity=0.5,
line=dict(color="rgb"+str(tableau20[3]),
width=2,
dash='dot')))
# Add dotted lines for forth button
figb.add_trace(go.Scatter(x=[-1, 0, 1, 2, 3, 4, 5, 6],
y=[line_7]*8,
mode='lines',
visible=False,
name='T<sub>1</sub>w mean',
opacity=0.5,
line=dict(color="rgb"+str(tableau20[0]),
width=2,
dash='dot')))
figb.add_trace(go.Scatter(x=[-1, 0, 1, 2, 3, 4, 5, 6],
y=[line_8]*8,
mode='lines',
visible=False,
name='T<sub>2</sub>w mean',
opacity=0.5,
line=dict(color="rgb"+str(tableau20[3]),
width=2,
dash='dot')))
x = [-1, 0, 1, 2, 3, 4, 5, 6]
x_rev = x[::-1]
std_1 = get_std(mean_area_matrix_1) # T1w mean area --- std
std_2 = get_std(mean_area_matrix_2) # T2w mean area --- std
std_3 = get_std(mean_ap_matrix_1) # T1w mean AP --- std
std_4 = get_std(mean_ap_matrix_2) # T2w mean AP --- std
std_5 = get_std(mean_rl_matrix_1) # T1w mean RL --- std
std_6 = get_std(mean_rl_matrix_2) # T2w mean RL --- std
std_7 = get_std(mean_angle_matrix_1) # T1w angle --- std
std_8 = get_std(mean_angle_matrix_2) # T2w angle --- std
# Add STD for 1 button
figb.add_trace(go.Scatter(
x=x+x_rev,
y=[line_1+std_1]*8+[line_1-std_1]*8,
fill='toself',
fillcolor='rgba(31, 119, 180,0.15)',
line_color='rgba(255,255,255,0)',
showlegend=False,
hoverinfo='skip',
name='T1w STD',
))
figb.add_trace(go.Scatter(
x=x+x_rev,
y=[line_2+std_2]*8+[line_2-std_2]*8,
fill='toself',
fillcolor='rgba(255, 187, 120,0.15)',
line_color='rgba(255,255,255,0)',
showlegend=False,
hoverinfo='skip',
name='T2w STD',
))
# Add STD for 2 button
figb.add_trace(go.Scatter(
x=x+x_rev,
y=[line_3+std_3]*8+[line_3-std_3]*8,
fill='toself',
visible=False,
fillcolor='rgba(31, 119, 180,0.15)',
line_color='rgba(255,255,255,0)',
showlegend=False,
hoverinfo='skip',
name='T1w STD',
))
figb.add_trace(go.Scatter(
x=x+x_rev,
y=[line_4+std_4]*8+[line_4-std_4]*8,
fill='toself',
visible=False,
fillcolor='rgba(255, 187, 120,0.15)',
line_color='rgba(255,255,255,0)',
showlegend=False,
hoverinfo='skip',
name='T1w STD',
))
# Add STD for 3 button
figb.add_trace(go.Scatter(
x=x+x_rev,
y=[line_5+std_5]*8+[line_5-std_5]*8,
fill='toself',
visible=False,
fillcolor='rgba(31, 119, 180,0.15)',
line_color='rgba(255,255,255,0)',
showlegend=False,
hoverinfo='skip',
name='T1w STD',
))
figb.add_trace(go.Scatter(
x=x+x_rev,
y=[line_6+std_6]*8+[line_6-std_6]*8,
fill='toself',
visible=False,
fillcolor='rgba(255, 187, 120,0.15)',
line_color='rgba(255,255,255,0)',
showlegend=False,
hoverinfo='skip',
name='T1w STD',
))
# Add STD for 4 button
figb.add_trace(go.Scatter(
x=x+x_rev,
y=[line_7+std_7]*8+[line_7-std_7]*8,
fill='toself',
visible=False,
fillcolor='rgba(31, 119, 180,0.15)',
line_color='rgba(255,255,255,0)',
showlegend=False,
hoverinfo='skip',
name='T1w STD',
))
figb.add_trace(go.Scatter(
x=x+x_rev,
y=[line_8+std_8]*8+[line_8-std_8]*8,
fill='toself',
visible=False,
fillcolor='rgba(255, 187, 120,0.15)',
line_color='rgba(255,255,255,0)',
showlegend=False,
hoverinfo='skip',
name='T1w STD',
))
figb.update_layout(title = ' Spinal cord CSA [T<sub>1</sub>w/T<sub>2</sub>w]',
updatemenus=[
dict(
active = 0,
x=1.32,
y=0.58,
direction="down",
yanchor="top",
buttons=list([
dict(label="(1) Mean (area)",
method="update",
args=[{"visible": [True] + [True]*12 + [False]*36 + [True]*2 + [False]*6 + [True]*2 + [False]*6},
{"yaxis": dict(range=[0,100],
title='mm<sup>2</sup>',
mirror=True,
ticks='outside',
showline=True,
linecolor='#000',
tickfont = dict(size=16))}]),
dict(label="(2) Mean (AP)",
method="update",
args=[{"visible": [True] + [False]*12 + [True]*12 + [False]*24 + [False]*2 + [True]*2 +[False]*4 + [False]*2 + [True]*2 +[False]*4},
{"yaxis": dict(range=[0,15],
title='mm',
mirror=True,
ticks='outside',
showline=True,
linecolor='#000',
tickfont = dict(size=16))}]),
dict(label="(3) Mean (RL)",
method="update",
args=[{"visible": [True] + [False]*24 + [True]*12 + [False]*12 + [False]*4 + [True]*2 +[False]*2 + [False]*4 + [True]*2 +[False]*2},
{"yaxis": dict(range=[0,15],
title='mm',
mirror=True,
ticks='outside',
showline=True,
linecolor='#000',
tickfont = dict(size=16))}]),
dict(label="(4) Mean (angle)",
method="update",
args=[{"visible": [True] + [False]*36 + [True]*12 + [False]*6 + [True]*2 + [False]*6 + [True]*2 },
{"yaxis": dict(range=[-10,15],
title='degrees (°)',
mirror=True,
ticks='outside',
showline=True,
linecolor='#000',
tickfont = dict(size=16))}]) ]) )],
title_x = 0.445,
legend=dict(orientation = 'v',
bordercolor="Gray",
borderwidth=1),
xaxis=dict(range=[-0.45,5.45],
mirror=True,
ticks='outside',
showline=True,
linecolor='#000',
tickvals = [0, 1, 2, 3, 4, 5],
ticktext = labels_subjects,
tickfont = dict(size=12)),
yaxis_title='mm<sup>2</sup>',
yaxis=dict(range=[0,100],
mirror=True,
ticks='outside',
showline=True,
linecolor='#000',
tickfont = dict(size=14)),
annotations=[
dict(text="Display metric: ",
showarrow=False,
x=1.25,
y=0.62,
xref = 'paper',
yref="paper")],
plot_bgcolor='rgba(227,233,244, 0.5)',
width = 760,
height = 520,
font = dict(size = 13),
margin=go.layout.Margin(l=50,
r=50,
b=60,
t=35))
# Plot figure
# For jupyter-book rendering --=-- jupyter-lab
plot(figb, filename = 'new-fig.html', config = config)
display(HTML('new-fig.html'))
# For local jupyter notebook --== binder session
# iplot(figb,config=config)
import plotly.graph_objects as go
import plotly.tools as tls
from plotly.offline import plot, iplot, init_notebook_mode
from plotly.validators.scatter.marker import SymbolValidator
from IPython.core.display import display, HTML
import numpy as np
import pandas as pd
# Add plotly
init_notebook_mode(connected = True)
config={'showLink': False, 'displayModeBar': False}
# Load the data
df_3 = pd.read_csv("./spinalcord_results/csa-GM_T2s.csv", converters={'project_id': lambda x: str(x)})
# Insert new columns for Subject and Session and start inserting values
df_3.insert(0, "Subject", "Any")
df_3.insert(1, "Session", "Any")
# Get Subject and Session from csv
for index, row in df_3.iterrows():
subject = int(row['Filename'].split("/")[6].split('-')[1])
session = int(row['Filename'].split("/")[7].split("-")[1])
df_3.at[index, 'Subject'] = subject
df_3.at[index, 'Session'] = session
# Sort values based on Subject -- Session
df_3 = df_3.sort_values(['Subject', 'Session'], ascending=[True, True])
# Define lists for metrics
mean_area_matrix_1 = []
# Get the values for all 4 metric [area, mean_AP, mean_RL, angle_AP]
for i in range(0, 6, 1):
sub_values = df_3.loc[df_3['Subject'] == i+1]
mean_area_ses = []
for j in range(0, 4, 1):
ses_values = sub_values.loc[sub_values['Session'] == j+1]
mean_area = -100
for index, row in ses_values.iterrows():
# Read values
MEAN_area = row['MEAN(area)']
# Store values
mean_area = MEAN_area
# Append values to lists for sessions
mean_area_ses.append(mean_area)
# Append session lists to main matrices for each metric
mean_area_matrix_1.append(mean_area_ses)
# Functions for mean and std
def get_mean(mean_matrix):
temp = mean_matrix[::]
mean_list = []
for ele in temp:
ele = [i for i in ele if i!=-100]
mean_list.extend(ele)
mean = float('{0:.2f}'.format(np.mean(mean_list)))
return mean
def get_std(mean_matrix):
temp = mean_matrix[::]
mean_list = []
for ele in temp:
ele = [i for i in ele if i!=-100]
mean_list.extend(ele)
std = float('{0:.3f}'.format(np.std(mean_list)))
return std
# Get different symbols (See for reference: https://plotly.com/python/marker-style/)
raw_symbols = SymbolValidator().values
namestems = []
namevariants = []
symbols = []
for i in range(0,len(raw_symbols),3):
name = raw_symbols[i+2]
symbols.append(raw_symbols[i])
namestems.append(name.replace("-open", "").replace("-dot", ""))
namevariants.append(name[len(namestems[-1]):])
# Load fancy colors
tableau20 = [(31, 119, 180), (174, 199, 232), (255, 127, 14), (255, 187, 120),
(44, 160, 44), (152, 223, 138), (214, 39, 40), (255, 152, 150),
(148, 103, 189), (197, 176, 213), (140, 86, 75), (196, 156, 148),
(227, 119, 194), (247, 182, 210), (127, 127, 127), (199, 199, 199),
(188, 189, 34), (219, 219, 141), (23, 190, 207), (158, 218, 229)]
# Define lists needed for plotting
t1 = [-0.2, -0.06, 0.08, 0.22]
t2 = [0 -0.2 + i*0.14 for i in range(0, 4)]
labels =["Session 1", "Session 2","Session 3","Session 4"]
labels_subjects = ['Subject 1', 'Subject 2', 'Subject 3', 'Subject 4', 'Subject 5', 'Subject 6']
labels_int = [i for i in range(1, 7)]
x_rev = labels_int[::-1]
# Add first values for labels [Sub1...Sub6]
figb = go.Figure(data=go.Scatter(x=labels_int,
y=[-1000, -1000, -1000, -1000, -1000, -1000],
mode='markers',
showlegend=False,
marker_color='red'))
# Add MEAN [area] --- > T1w
for trace in range(0, len(mean_area_matrix_1)):
t = [trace -0.2 + i*0.14 for i in range(0, 4)]
if trace == 0:
figb.add_trace(go.Scatter(x=t,
y=mean_area_matrix_1[trace],
mode='markers',
legendgroup="group1",
hovertemplate =
"Mean (area): <i> %{y: .2f} </i> mm<sup>2</sup>" +
"<br>" +
"<b>%{text}</b>",
showlegend = True,
text = ['Session {}'.format(i + 1) for i in range(4)],
name= 'T<sub>2</sub>s',
marker_color="rgb"+str(tableau20[0])))
else:
figb.add_trace(go.Scatter(x=t,
y=mean_area_matrix_1[trace],
mode='markers',
legendgroup="group1",
showlegend = False,
hovertemplate =
"Mean (area): <i> %{y: .2f} </i> mm<sup>2</sup>" +
"<br>" +
"<b>%{text}</b>",
text = ['Session {}'.format(i + 1) for i in range(4)],
name='T<sub>2</sub>s',
marker_color="rgb"+str(tableau20[0])))
# Calculate means
line_1 = get_mean(mean_area_matrix_1) # T2s mean area --- mean
# Add dotted lines for first button
figb.add_trace(go.Scatter(x=[-1, 0, 1, 2, 3, 4, 5, 6],
y=[line_1]*8,
mode='lines',
name='T<sub>2</sub>s mean',
opacity=0.5,
line=dict(color="rgb"+str(tableau20[0]),
width=2,
dash='dot')))
x = [-1, 0, 1, 2, 3, 4, 5, 6]
x_rev = x[::-1]
std_1 = get_std(mean_area_matrix_1) # T1s mean area --- std
# Add STD for 1 button
figb.add_trace(go.Scatter(
x=x+x_rev,
y=[line_1+std_1]*8+[line_1-std_1]*8,
fill='toself',
fillcolor='rgba(31, 119, 180,0.15)',
line_color='rgba(255,255,255,0)',
showlegend=False,
hoverinfo='skip',
name='T2s STD',
))
figb.update_layout(title = 'Spinal cord gray matter CSA',
title_x = 0.5,
showlegend=False,
xaxis=dict(range=[-0.45,5.45],
mirror=True,
ticks='outside',
showline=True,
linecolor='#000',
tickvals = [0, 1, 2, 3, 4, 5],
ticktext = labels_subjects,
tickfont = dict(size=12)),
yaxis_title='mm<sup>2</sup>',
yaxis=dict(range=[0,25],
mirror=True,
ticks='outside',
showline=True,
linecolor='#000',
tickfont = dict(size=14)),
plot_bgcolor='rgba(227,233,244, 0.5)',
width = 640,
height = 520,
font = dict(size = 12),
margin=go.layout.Margin(l=50,
r=50,
b=60,
t=35))
# Plot figure
# For jupyter-book rendering --=-- jupyter-lab
plot(figb, filename = 'new-fig-2.html', config = config)
display(HTML('new-fig-2.html'))
# For local jupyter notebook --== binder session
# iplot(figb,config=config)
import plotly.graph_objects as go
import plotly.tools as tls
from plotly.offline import plot, iplot, init_notebook_mode
from plotly.validators.scatter.marker import SymbolValidator
from IPython.core.display import display, HTML
import numpy as np
import pandas as pd
# Add plotly
init_notebook_mode(connected = True)
config={'showLink': False, 'displayModeBar': False}
# Read data for (DWI_FA, DWI_MD, DWI_RD, MTR, MTsat, T1)
df_dwi_fa = pd.read_csv("./spinalcord_results/DWI_FA.csv", converters={'project_id': lambda x: str(x)})
df_dwi_md = pd.read_csv("./spinalcord_results/DWI_MD.csv", converters={'project_id': lambda x: str(x)})
df_dwi_rd = pd.read_csv("./spinalcord_results/DWI_RD.csv", converters={'project_id': lambda x: str(x)})
df_mtr = pd.read_csv("./spinalcord_results/MTR.csv", converters={'project_id': lambda x: str(x)})
df_mtsat = pd.read_csv("./spinalcord_results/MTsat.csv", converters={'project_id': lambda x: str(x)})
df_t1_2 = pd.read_csv("./spinalcord_results/T1.csv", converters={'project_id': lambda x: str(x)})
# Function for reading session values
def get_sessions_values(df, metric):
'''
:param df: pandas dataframe with results
:param metric: column in dataframe
:return: session values as matrix
'''
df.insert(0, "Subject", "Any")
df.insert(1, "Session", "Any")
# Get Subject and Session from csv
for index, row in df.iterrows():
subject = int(row['Filename'].split("/")[6].split('-')[1])
session = int(row['Filename'].split("/")[7].split("-")[1])
df.at[index, 'Subject'] = subject
df.at[index, 'Session'] = session
# Sort values based on Subject -- Session
df_2 = df.sort_values(['Subject', 'Session'], ascending=[True, True])
# Define lists for metrics
matrix_1 = []
# Get the values for all desired column (metric)
for i in range(0, 6, 1):
sub_values = df_2.loc[df_2['Subject'] == i + 1]
ses = []
for j in range(0, 4, 1):
ses_values = sub_values.loc[sub_values['Session'] == j + 1]
temp = -100
for index, row in ses_values.iterrows():
# Read values
my_value = row[metric]
# Store values
temp = my_value
# Append values to lists for sessions
ses.append(temp)
# Append session lists to main matrices for each metric
matrix_1.append(ses)
return matrix_1
# Get values for sessions, store in lists
matrix_dwi_fa = get_sessions_values(df=df_dwi_fa,metric="WA()")
matrix_dwi_md = get_sessions_values(df=df_dwi_md, metric="WA()")
matrix_dwi_rd = get_sessions_values(df=df_dwi_rd, metric="WA()")
matrix_mtr = get_sessions_values(df=df_mtr, metric="WA()")
matrix_mtsat = get_sessions_values(df=df_mtsat, metric="WA()")
matrix_t1_2 = get_sessions_values(df=df_t1_2, metric="WA()")
# Functions for calculating mean and std from lists
def get_mean(mean_matrix):
temp = mean_matrix[::]
mean_list = []
for ele in temp:
ele = [i for i in ele if i!=-100]
mean_list.extend(ele)
mean = float('{0:.7f}'.format(np.mean(mean_list)))
return mean
def get_std(mean_matrix):
temp = mean_matrix[::]
mean_list = []
for ele in temp:
ele = [i for i in ele if i!=-100]
mean_list.extend(ele)
std = float('{0:.7}'.format(np.std(mean_list)))
return std
# Get different symbols (See for reference: https://plotly.com/python/marker-style/)
raw_symbols = SymbolValidator().values
namestems = []
namevariants = []
symbols = []
for i in range(0,len(raw_symbols),3):
name = raw_symbols[i+2]
symbols.append(raw_symbols[i])
namestems.append(name.replace("-open", "").replace("-dot", ""))
namevariants.append(name[len(namestems[-1]):])
# Load fancy colors
tableau20 = [(31, 119, 180), (174, 199, 232), (255, 127, 14), (255, 187, 120),
(44, 160, 44), (152, 223, 138), (214, 39, 40), (255, 152, 150),
(148, 103, 189), (197, 176, 213), (140, 86, 75), (196, 156, 148),
(227, 119, 194), (247, 182, 210), (127, 127, 127), (199, 199, 199),
(188, 189, 34), (219, 219, 141), (23, 190, 207), (158, 218, 229)]
# Define lists needed for plotting
t1 = [-0.2, -0.06, 0.08, 0.22]
t2 = [0 -0.2 + i*0.14 for i in range(0, 4)]
labels =["Session 1", "Session 2","Session 3","Session 4"]
labels_subjects = ['Subject 1', 'Subject 2', 'Subject 3', 'Subject 4', 'Subject 5', 'Subject 6']
labels_int = [i for i in range(1, 7)]
x_rev = labels_int[::-1]
# Add first values for labels [Sub1...Sub6]
figb = go.Figure(data=go.Scatter(x=labels_int,
y=[-1000, -1000, -1000, -1000, -1000, -1000],
mode='markers',
showlegend=False,
marker_color='red'))
# Add DWI_FA
for trace in range(0, len(matrix_dwi_fa)):
t = [trace -0.2 + i*0.14 for i in range(0, 4)]
if trace == 0:
figb.add_trace(go.Scatter(x=t,
y=matrix_dwi_fa[trace],
mode='markers',
legendgroup="group1",
hovertemplate =
"WA(): <i> %{y: .2f} </i>" +
"<br>" +
"<b>%{text}</b>",
showlegend = True,
text = ['Session {}'.format(i + 1) for i in range(4)],
name= 'DWI_FA',
marker_color="rgb"+str(tableau20[0])))
else:
figb.add_trace(go.Scatter(x=t,
y=matrix_dwi_fa[trace],
mode='markers',
legendgroup="group1",
showlegend = False,
hovertemplate =
"WA(): <i> %{y: .2f}" +
"<br>" +
"<b>%{text}</b>",
text = ['Session {}'.format(i + 1) for i in range(4)],
name='DWI_FA',
marker_color="rgb"+str(tableau20[0])))
# Add DWI_MD
for trace in range(0, len(matrix_dwi_md)):
t = [trace -0.2 + i*0.14 for i in range(0, 4)]
if trace == 0:
figb.add_trace(go.Scatter(x=t,
y=matrix_dwi_md[trace],
mode='markers',
visible=False,
legendgroup="group1",
hovertemplate =
"WA(): <i> %{y: .6f} </i> mm<sup>2</sup>/s" +
"<br>" +
"<b>%{text}</b>",
showlegend = True,
text = ['Session {}'.format(i + 1) for i in range(4)],
name= 'DWI_MD',
marker_color="rgb"+str(tableau20[0])))
else:
figb.add_trace(go.Scatter(x=t,
y=matrix_dwi_md[trace],
mode='markers',
visible=False,
legendgroup="group1",
showlegend = False,
hovertemplate =
"WA(): <i> %{y: .6f} mm<sup>2</sup>/s" +
"<br>" +
"<b>%{text}</b>",
text = ['Session {}'.format(i + 1) for i in range(4)],
name='DWI_MD',
marker_color="rgb"+str(tableau20[0])))
# Add DWI_RD
for trace in range(0, len(matrix_dwi_rd)):
t = [trace -0.2 + i*0.14 for i in range(0, 4)]
if trace == 0:
figb.add_trace(go.Scatter(x=t,
y=matrix_dwi_rd[trace],
mode='markers',
visible=False,
legendgroup="group1",
hovertemplate =
"WA(): <i> %{y: .6f} </i> mm<sup>2</sup>/s" +
"<br>" +
"<b>%{text}</b>",
showlegend = True,
text = ['Session {}'.format(i + 1) for i in range(4)],
name= 'DWI_RD',
marker_color="rgb"+str(tableau20[0])))
else:
figb.add_trace(go.Scatter(x=t,
y=matrix_dwi_rd[trace],
mode='markers',
visible=False,
legendgroup="group1",
showlegend = False,
hovertemplate =
"WA(): <i> %{y: .6f} mm<sup>2</sup>/s" +
"<br>" +
"<b>%{text}</b>",
text = ['Session {}'.format(i + 1) for i in range(4)],
name='DWI_RD',
marker_color="rgb"+str(tableau20[0])))
# Add MTR
for trace in range(0, len(matrix_mtr)):
t = [trace -0.2 + i*0.14 for i in range(0, 4)]
if trace == 0:
figb.add_trace(go.Scatter(x=t,
y=matrix_mtr[trace],
mode='markers',
visible=False,
legendgroup="group1",
hovertemplate =
"WA(): <i> %{y: .2f} </i>" +
"<br>" +
"<b>%{text}</b>",
showlegend = True,
text = ['Session {}'.format(i + 1) for i in range(4)],
name= 'MTR',
marker_color="rgb"+str(tableau20[0])))
else:
figb.add_trace(go.Scatter(x=t,
y=matrix_mtr[trace],
mode='markers',
visible=False,
legendgroup="group1",
showlegend = False,
hovertemplate =
"WA(): <i> %{y: .2f}" +
"<br>" +
"<b>%{text}</b>",
text = ['Session {}'.format(i + 1) for i in range(4)],
name='MTR',
marker_color="rgb"+str(tableau20[0])))
# Add MTsat
for trace in range(0, len(matrix_mtsat)):
t = [trace -0.2 + i*0.14 for i in range(0, 4)]
if trace == 0:
figb.add_trace(go.Scatter(x=t,
y=matrix_mtsat[trace],
mode='markers',
visible=False,
legendgroup="group1",
hovertemplate =
"WA(): <i> %{y: .2f} </i>" +
"<br>" +
"<b>%{text}</b>",
showlegend = True,
text = ['Session {}'.format(i + 1) for i in range(4)],
name= 'MTsat',
marker_color="rgb"+str(tableau20[0])))
else:
figb.add_trace(go.Scatter(x=t,
y=matrix_mtsat[trace],
mode='markers',
visible=False,
legendgroup="group1",
showlegend = False,
hovertemplate =
"WA(): <i> %{y: .2f}" +
"<br>" +
"<b>%{text}</b>",
text = ['Session {}'.format(i + 1) for i in range(4)],
name='MTsat',
marker_color="rgb"+str(tableau20[0])))
# Add T1
for trace in range(0, len(matrix_t1_2)):
t = [trace -0.2 + i*0.14 for i in range(0, 4)]
if trace == 0:
figb.add_trace(go.Scatter(x=t,
y=matrix_t1_2[trace],
mode='markers',
visible=False,
legendgroup="group1",
hovertemplate =
"WA(): <i> %{y: .7f} </i> sec" +
"<br>" +
"<b>%{text}</b>",
showlegend = True,
text = ['Session {}'.format(i + 1) for i in range(4)],
name= 'T<sub>1</sub>',
marker_color="rgb"+str(tableau20[0])))
else:
figb.add_trace(go.Scatter(x=t,
y=matrix_t1_2[trace],
mode='markers',
visible=False,
legendgroup="group1",
showlegend = False,
hovertemplate =
"WA(): <i> %{y: .7f} sec" +
"<br>" +
"<b>%{text}</b>",
text = ['Session {}'.format(i + 1) for i in range(4)],
name='T<sub>1</sub>',
marker_color="rgb"+str(tableau20[0])))
# Calculate means
line_1 = get_mean(matrix_dwi_fa) # DWI_FA --- mean
line_2 = get_mean(matrix_dwi_md) # DWI_MD --- mean
line_3 = get_mean(matrix_dwi_rd) # DWI_RD --- mean
line_4 = get_mean(matrix_mtr) # MTR --- mean
line_5 = get_mean(matrix_mtsat) # MTsat --- mean
line_6 = get_mean(matrix_t1_2) # T1 --- mean
# Add dotted lines for buttons
figb.add_trace(go.Scatter(x=[-1, 0, 1, 2, 3, 4, 5, 6],
y=[line_1]*8,
mode='lines',
name='DWI_FA mean',
opacity=0.5,
line=dict(color="rgb"+str(tableau20[0]),
width=2,
dash='dot')))
figb.add_trace(go.Scatter(x=[-1, 0, 1, 2, 3, 4, 5, 6],
y=[line_2]*8,
mode='lines',
visible=False,
name='DWI_MD mean',
opacity=0.5,
line=dict(color="rgb"+str(tableau20[0]),
width=2,
dash='dot')))
figb.add_trace(go.Scatter(x=[-1, 0, 1, 2, 3, 4, 5, 6],
y=[line_3]*8,
mode='lines',
visible=False,
name='DWI_RD mean',
opacity=0.5,
line=dict(color="rgb"+str(tableau20[0]),
width=2,
dash='dot')))
figb.add_trace(go.Scatter(x=[-1, 0, 1, 2, 3, 4, 5, 6],
y=[line_4]*8,
mode='lines',
visible=False,
name='MTR mean',
opacity=0.5,
line=dict(color="rgb"+str(tableau20[0]),
width=2,
dash='dot')))
figb.add_trace(go.Scatter(x=[-1, 0, 1, 2, 3, 4, 5, 6],
y=[line_5]*8,
mode='lines',
visible=False,
name='MTsat mean',
opacity=0.5,
line=dict(color="rgb"+str(tableau20[0]),
width=2,
dash='dot')))
figb.add_trace(go.Scatter(x=[-1, 0, 1, 2, 3, 4, 5, 6],
y=[line_6]*8,
mode='lines',
visible=False,
name='T<sub>1</sub> mean',
opacity=0.5,
line=dict(color="rgb"+str(tableau20[0]),
width=2,
dash='dot')))
x = [-1, 0, 1, 2, 3, 4, 5, 6]
x_rev = x[::-1]
std_1 = get_std(matrix_dwi_fa) # DWI_FA --- std
std_2 = get_std(matrix_dwi_md) # DWI_MD --- std
std_3 = get_std(matrix_dwi_rd) # DWI_RD --- std
std_4 = get_std(matrix_mtr) # MTR --- std
std_5 = get_std(matrix_mtsat) # MTsat --- std
std_6 = get_std(matrix_t1_2) # T1 --- std
# Add STD for buttons
figb.add_trace(go.Scatter(
x=x+x_rev,
y=[line_1+std_1]*8+[line_1-std_1]*8,
fill='toself',
fillcolor='rgba(31, 119, 180,0.15)',
line_color='rgba(255,255,255,0)',
showlegend=False,
hoverinfo='skip',
name='',
))
figb.add_trace(go.Scatter(
x=x+x_rev,
y=[line_2+std_2]*8+[line_2-std_2]*8,
fill='toself',
fillcolor='rgba(31, 119, 180,0.15)',
line_color='rgba(255,255,255,0)',
showlegend=False,
hoverinfo='skip',
name='',
))
# Add STD for 2 button
figb.add_trace(go.Scatter(
x=x+x_rev,
y=[line_3+std_3]*8+[line_3-std_3]*8,
fill='toself',
visible=False,
fillcolor='rgba(31, 119, 180,0.15)',
line_color='rgba(255,255,255,0)',
showlegend=False,
hoverinfo='skip',
name='',
))
figb.add_trace(go.Scatter(
x=x+x_rev,
y=[line_4+std_4]*8+[line_4-std_4]*8,
fill='toself',
visible=False,
fillcolor='rgba(31, 119, 180,0.15)',
line_color='rgba(255,255,255,0)',
showlegend=False,
hoverinfo='skip',
name='',
))
# Add STD for 3 button
figb.add_trace(go.Scatter(
x=x+x_rev,
y=[line_5+std_5]*8+[line_5-std_5]*8,
fill='toself',
visible=False,
fillcolor='rgba(31, 119, 180,0.15)',
line_color='rgba(255,255,255,0)',
showlegend=False,
hoverinfo='skip',
name='',
))
figb.add_trace(go.Scatter(
x=x+x_rev,
y=[line_6+std_6]*8+[line_6-std_6]*8,
fill='toself',
visible=False,
fillcolor='rgba(31, 119, 180,0.15)',
line_color='rgba(255,255,255,0)',
showlegend=False,
hoverinfo='skip',
name='',
))
figb.update_layout(title = 'Spinal cord qMRI microstructure ',
updatemenus=[
dict(
active = 0,
x=1.27,
y=0.58,
direction="down",
yanchor="top",
buttons=list([
dict(label="(1) DWI_FA",
method="update",
args=[{"visible": [True] + [True]*6 + [False]*30 + [True]*1 + [False]*5 + [True]*1 + [False]*5},
{"yaxis": dict(range=[0,1.6],
title='',
mirror=True,
ticks='outside',
showline=True,
linecolor='#000',
tickfont = dict(size=16))}]),
dict(label="(2) DWI_MD",
method="update",
args=[{"visible": [True] + [False]*6 + [True]*6 + [False]*24 + [False]*1 + [True]*1 +[False]*4 + [False]*1 + [True]*1 +[False]*4},
{"yaxis": dict(range=[0,0.0025],
title='mm<sup>2</sup>/s',
mirror=True,
ticks='outside',
showline=True,
linecolor='#000',
tickfont = dict(size=16))}]),
dict(label="(3) DWI_RD",
method="update",
args=[{"visible": [True] + [False]*12 + [True]*6 + [False]*18 + [False]*2 + [True]*1 +[False]*3 + [False]*2 + [True]*1 +[False]*3},
{"yaxis": dict(range=[0,0.0025],
title='mm<sup>2</sup>/s',
mirror=True,
ticks='outside',
showline=True,
linecolor='#000',
tickfont = dict(size=16))}]),
dict(label="(4) MTR",
method="update",
args=[{"visible": [True] + [False]*18 + [True]*6 + [False]*12 + [False]*3 + [True]*1 +[False]*2 + [False]*3 + [True]*1 +[False]*2},
{"yaxis": dict(range=[0,60],
title='',
mirror=True,
ticks='outside',
showline=True,
linecolor='#000',
tickfont = dict(size=16))}]),
dict(label="(5) MTsat",
method="update",
args=[{"visible": [True] + [False]*24 + [True]*6 + [False]*6 + [False]*4 + [True]*1 +[False]*1 + [False]*4 + [True]*1 +[False]*1},
{"yaxis": dict(range=[0,6],
title='',
mirror=True,
ticks='outside',
showline=True,
linecolor='#000',
tickfont = dict(size=16))}]),
dict(label="(6) T<sub>1</sub>",
method="update",
args=[{"visible": [True] + [False]*30 + [True]*6 + [False]*5 + [True]*1 + [False]*5 + [True]*1 },
{"yaxis": dict(range=[0,0.0025],
title='s (seconds)',
mirror=True,
ticks='outside',
showline=True,
linecolor='#000',
tickfont = dict(size=16))}]) ]) )],
title_x = 0.445,
legend=dict(orientation = 'v',
bordercolor="Gray",
borderwidth=1),
xaxis=dict(range=[-0.45,5.45],
mirror=True,
ticks='outside',
showline=True,
linecolor='#000',
tickvals = [0, 1, 2, 3, 4, 5],
ticktext = labels_subjects,
tickfont = dict(size=12)),
yaxis_title='',
yaxis=dict(range=[0,1.6],
mirror=True,
ticks='outside',
showline=True,
linecolor='#000',
tickfont = dict(size=14)),
annotations=[
dict(text="Display metric: ",
showarrow=False,
x=1.25,
y=0.62,
xref = 'paper',
yref="paper")],
plot_bgcolor='rgba(227,233,244, 0.5)',
width = 760,
height = 520,
font = dict(size = 13),
margin=go.layout.Margin(l=50,
r=50,
b=60,
t=35))
# Plot figure
# For jupyter-book rendering --=-- jupyter-lab
plot(figb, filename = 'new-fig-3.html', config = config)
display(HTML('new-fig-3.html'))
# For local jupyter notebook --== binder session
# iplot(figb,config=config)